{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "bdaa1f22-ffff-4ef5-a51f-329a908b7e98",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "source": [
    "Copyright (c) MONAI Consortium  \n",
    "Licensed under the Apache License, Version 2.0 (the \"License\");  \n",
    "you may not use this file except in compliance with the License.  \n",
    "You may obtain a copy of the License at  \n",
    "&nbsp;&nbsp;&nbsp;&nbsp;http://www.apache.org/licenses/LICENSE-2.0  \n",
    "Unless required by applicable law or agreed to in writing, software  \n",
    "distributed under the License is distributed on an \"AS IS\" BASIS,  \n",
    "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.  \n",
    "See the License for the specific language governing permissions and  \n",
    "limitations under the License.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6923e88c-10a0-4285-a797-3d3a6ed4c60c",
   "metadata": {},
   "source": [
    "# SPADE VAE-GAN\n",
    "\n",
    "In this tutorial, we apply SPADE, a VAE-GAN-based neural network developed by Park et al. [1] that performs semantic image synthesis. We apply to a subset of BraTS [2] that we registered to MNI space and resampled to 2mm isotropic space. Segmentations of cerebrospinal fluid, grey and white matter, deep grey matter and brainstem were obtained using Geodesic Information Flows (GIF) [3].\n",
    "\n",
    "[1] Park, T., Liu, M.-Y., Wang, T.-C., & Zhu, J.-Y. (2019). Semantic Image Synthesis with Spatially-Adaptive Normalization. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.\n",
    "\n",
    "[2] Menze, B. H., Jakab, A., Bauer, S., Kalpathy-Cramer, J., Farahani, K., Kirby, J., Burren, Y., Porz, N., Slotboom, J., Wiest, R., Lanczi, L., Gerstner, E., Weber, M.-A., Arbel, T., Avants, B. B., Ayache, N., Buendia, P., Collins, D. L., Cordier, N., … van Leemput, K. (2015). The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS). IEEE Transactions on Medical Imaging, 34(10), 1993–2024. https://doi.org/10.1109/TMI.2014.2377694\n",
    "\n",
    "[3] Cardoso, M. J., Wolz, R., Modat, M., Fox, N. C., Rueckert, D., & Ourselin, S. (2012). Geodesic information flows. Medical Image Computing and Computer-Assisted Intervention : MICCAI ...  International Conference on Medical Image Computing and Computer-Assisted Intervention, 15(Pt 2), 262–270. https://doi.org/10.1007/978-3-642-33418-4_33"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a3604c287a30a2b4",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "source": [
    "## Setup environment "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6732a08b84ec442",
   "metadata": {
    "collapsed": false,
    "is_executing": true,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "!python -c \"import monai\" || pip install -q \"monai-weekly[tqdm]\"\n",
    "!python -c \"import matplotlib\" || pip install -q matplotlib\n",
    "!python -c \"import gdown\" || pip install -q gdown\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16e7adac407b6c34",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "source": [
    "## Setup imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1bb9ef03-4d0d-4c04-9bd9-e399e1b37b86",
   "metadata": {
    "is_executing": true
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import tempfile\n",
    "import zipfile\n",
    "from pathlib import Path\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import torch\n",
    "import gdown\n",
    "import monai\n",
    "from monai.config import print_config\n",
    "from monai.utils import set_determinism\n",
    "from monai.data import DataLoader\n",
    "from monai.networks.nets import SPADENet, MultiScalePatchDiscriminator\n",
    "from monai.losses import PatchAdversarialLoss, PerceptualLoss\n",
    "\n",
    "print_config()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e8e9a502-32f7-426a-aa98-5d9c56952f14",
   "metadata": {},
   "source": [
    "## Set-up a data directory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ec734e87-1415-40a7-98a6-a53ddf6350d9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Temporary directory used: /tmp/tmpewems660 \n"
     ]
    }
   ],
   "source": [
    "directory = os.environ.get(\"MONAI_DATA_DIRECTORY\")\n",
    "root_dir = tempfile.mkdtemp() if directory is None else directory\n",
    "root_dir = Path(root_dir)\n",
    "print(\"Temporary directory used: %s \" % root_dir)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e68de24df72cd5d",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "source": [
    "## Set deterministic training for reproducibility"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9b0659759c18728f",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "set_determinism(42)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a98c6cf-b38e-4cba-8fb3-e07f67d0ec71",
   "metadata": {},
   "source": [
    "## Description of data and download dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11e6cd5c-7bf9-47ce-93dc-c7760f1bae9e",
   "metadata": {},
   "source": [
    "### Description of the data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "00d8b3be-8e21-4d8b-898e-2784c0d7640c",
   "metadata": {},
   "source": [
    "The data for this notebook comes from the brain tumour segmentation challenge (BraTS) [2]. The images have been registered to MNI space using ANTsPy, and then subsampled to 2mm isotropic resolution. Geodesic Information Flows (GIF) [3] has been used to segment 5 regions: cerebrospinal fluid (CSF), grey matter (GM), white matter (WM), deep grey matter (DGM) and brainstem. Tumour sub-layers were delineated manually as part of the challenge source data. \n",
    "In this subset, we have only used one MRI modality , T1. \n",
    "Segmentations in this subset are merged and consist of the following labels: 0 (background), 1 (CSF), 2 (GM), 3 (WM), 4 (DGM), 5 (brainstem), 6 (brainstem), 7 (non GD-enahncing tumour core), 8 (peritumoural oedema), 9 (GD-enhancing tumour)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "88d52103-9c87-491a-b1ed-e223bd455a34",
   "metadata": {},
   "source": [
    "### Download data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "84035825-1cad-45e9-ad64-02dba703ccec",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading...\n",
      "From (original): https://drive.google.com/uc?id=1q87a9euo52eoFG37shPK0G5juq20x7-m\n",
      "From (redirected): https://drive.google.com/uc?id=1q87a9euo52eoFG37shPK0G5juq20x7-m&confirm=t&uuid=ef27093b-8039-47a8-b710-81bee79688b4\n",
      "To: /tmp/tmpewems660/data.zip\n",
      "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 26.7M/26.7M [00:00<00:00, 27.8MB/s]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'/tmp/tmpewems660/data.zip'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Comment if already downloaded!\n",
    "gdown.download(\"https://drive.google.com/uc?id=1q87a9euo52eoFG37shPK0G5juq20x7-m\", os.path.join(root_dir, \"data.zip\"))\n",
    "#!gdown -O data.zip \"https://drive.google.com/uc?id=1q87a9euo52eoFG37shPK0G5juq20x7-m\" --remaining-ok"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c61496ac-6720-4bcf-b1b4-4c43fe7ea095",
   "metadata": {},
   "source": [
    "We extract and reorganise the data into the relevant sub-folders:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "20092100-c8f8-4d16-9481-3117157cd586",
   "metadata": {},
   "outputs": [],
   "source": [
    "zip_obj = zipfile.ZipFile(os.path.join(root_dir, \"data.zip\"), \"r\")\n",
    "zip_obj.extractall(root_dir)\n",
    "images_t1 = root_dir / \"BRATS_SUBS2_SUBSET/T1\"\n",
    "labels = root_dir / \"BRATS_SUBS2_SUBSET/Parcellations\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd6a4ecc-b9c4-4cd4-a17b-660a975e082a",
   "metadata": {},
   "source": [
    "## Prepare dataloaders"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4be3e840-da97-41d8-936b-b96bb264fc9a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# INPUT PARAMETERS\n",
    "input_shape = [128, 128]\n",
    "batch_size = 4\n",
    "num_workers = 2\n",
    "max_epochs = 100\n",
    "lambda_perc = 1.0\n",
    "lambda_feat = 0.1\n",
    "lambda_kld = 0.00001\n",
    "loss_adv = 1.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "7beeec55-d552-4f5c-bd56-d12475c1ca8f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# We create the data dictionaries that we need\n",
    "all_images = [os.path.join(images_t1, i) for i in os.listdir(images_t1)]\n",
    "np.random.shuffle(all_images)\n",
    "corresponding_labels = [\n",
    "    os.path.join(labels, i.split(\"/\")[-1].replace(i.split(\"/\")[-1].split(\"_\")[0], \"Parcellation\")) for i in all_images\n",
    "]\n",
    "input_dict = [{\"image\": i, \"label\": corresponding_labels[ind]} for ind, i in enumerate(all_images)]\n",
    "input_dict_train = input_dict[: int(len(input_dict) * 0.9)]\n",
    "input_dict_val = input_dict[int(len(input_dict) * 0.9) :]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be3237a9-082b-42fd-b3d4-cd3023edef3a",
   "metadata": {},
   "source": [
    "We define the relevant transforms:\n",
    "1. `LoadImaged`: to load the nii tumour images and labels\n",
    "2. `EnsureChannelFirstd`: to make sure that a channel dimension is added on the tensors\n",
    "3. `CenterSpatialCropd`: we ensure that the image and labels have the same shape\n",
    "4. `RandSpatialCropd`: because we are extracting 2D slices from 3D volumes, we crop slices\n",
    "5. `SqueezeDimd`: we remove the 1-dimension of the slice\n",
    "6. `Resized`: to bring the shape of all images to the same value\n",
    "7. `NormalizeIntensityd`: normalise the images\n",
    "8. `RandBiasFieldd`: bias field augmentation\n",
    "9. `RandAdjustContrastd`: random contrast augmentation\n",
    "10. `RandGaussianNoised`: random noise tradition\n",
    "11. `RandAffined`: random affine augmentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8b7e7a35-b6b1-4071-b450-443aeb0637f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "preliminar_shape = input_shape + [50]  # We take random slices fron the center of the brain\n",
    "crop_shape = input_shape + [1]\n",
    "base_transforms = [\n",
    "    monai.transforms.LoadImaged(keys=[\"label\", \"image\"]),\n",
    "    monai.transforms.EnsureChannelFirstd(keys=[\"image\", \"label\"]),\n",
    "    monai.transforms.CenterSpatialCropd(keys=[\"label\", \"image\"], roi_size=preliminar_shape),\n",
    "    monai.transforms.RandSpatialCropd(keys=[\"label\", \"image\"], roi_size=crop_shape, max_roi_size=crop_shape),\n",
    "    monai.transforms.SqueezeDimd(keys=[\"label\", \"image\"], dim=-1),\n",
    "    monai.transforms.Resized(keys=[\"label\", \"image\"], spatial_size=input_shape),\n",
    "]\n",
    "last_transforms = [\n",
    "    monai.transforms.NormalizeIntensityd(keys=[\"image\"]),\n",
    "    monai.transforms.ToTensord(keys=[\"image\", \"label\"]),\n",
    "]\n",
    "\n",
    "aug_transforms = [\n",
    "    monai.transforms.RandBiasFieldd(coeff_range=(0, 0.005), prob=0.33, keys=[\"image\"]),\n",
    "    monai.transforms.RandAdjustContrastd(gamma=(0.9, 1.15), prob=0.33, keys=[\"image\"]),\n",
    "    monai.transforms.RandGaussianNoised(prob=0.33, mean=0.0, std=np.random.uniform(0.005, 0.015), keys=[\"image\"]),\n",
    "    monai.transforms.RandAffined(\n",
    "        rotate_range=[-0.05, 0.05],\n",
    "        shear_range=[0.001, 0.05],\n",
    "        scale_range=[0, 0.05],\n",
    "        padding_mode=\"zeros\",\n",
    "        mode=\"nearest\",\n",
    "        prob=0.33,\n",
    "        keys=[\"label\", \"image\"],\n",
    "    ),\n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e08dd4d7-2b73-44f0-896c-66f1de7813b6",
   "metadata": {},
   "source": [
    "We create the dataset and dataloader:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "35c16de6-bf1b-490f-8768-a7041b6b1bd2",
   "metadata": {},
   "outputs": [],
   "source": [
    "train_transforms = monai.transforms.Compose(base_transforms + aug_transforms + last_transforms)\n",
    "val_transforms = monai.transforms.Compose(base_transforms + last_transforms)\n",
    "\n",
    "train_dataset = monai.data.dataset.Dataset(input_dict_train, train_transforms)\n",
    "val_dataset = monai.data.dataset.Dataset(input_dict_val, val_transforms)\n",
    "train_loader = DataLoader(train_dataset, shuffle=True, batch_size=batch_size, num_workers=num_workers)\n",
    "val_loader = DataLoader(val_dataset, shuffle=False, drop_last=False, batch_size=batch_size, num_workers=num_workers)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "69cdd8ec-6ea9-4e01-b488-a869909b3af7",
   "metadata": {},
   "source": [
    "We do a sanity check and plot an element of the dataset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "bf3c104c-3099-4d85-86f2-7563bf9f20d1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([4, 1, 128, 128])\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Sanity check\n",
    "batch = next(iter(train_loader))\n",
    "print(batch[\"image\"].shape)\n",
    "plt.subplot(1, 2, 1)\n",
    "plt.imshow(batch[\"image\"][0, 0, ...], cmap=\"gist_gray\")\n",
    "plt.axis(\"off\")\n",
    "plt.subplot(1, 2, 2)\n",
    "plt.imshow(batch[\"label\"][0, 0, ...], cmap=\"jet\")\n",
    "plt.axis(\"off\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dc34b150-bfad-4f23-9b00-409bebcf3fbc",
   "metadata": {},
   "source": [
    "### Networks creation and losses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "3e4fb2d3-c653-40a2-a4fa-2439ddf7f942",
   "metadata": {},
   "outputs": [],
   "source": [
    "device = \"cuda\" if torch.cuda.is_available() else \"cpu\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "2b67ff02-1d12-4256-ac79-7a4cd99bfe26",
   "metadata": {},
   "outputs": [],
   "source": [
    "def one_hot(input_label, label_nc):\n",
    "    # One hot encoding function for the labels\n",
    "    shape_ = list(input_label.shape)\n",
    "    shape_[1] = label_nc\n",
    "    label_out = torch.zeros(shape_)\n",
    "    for channel in range(label_nc):\n",
    "        label_out[:, channel, ...] = input_label[:, 0, ...] == channel\n",
    "    return label_out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "1033ac6e-b53e-4c13-9e7e-c2c88e5af220",
   "metadata": {},
   "outputs": [],
   "source": [
    "def picture_results(input_label, input_image, output_image):\n",
    "    plt.figure(figsize=(4, 1.5))\n",
    "    plt.subplot(1, 3, 1)\n",
    "    plt.imshow(torch.argmax(input_label, 1)[0, ...].detach().cpu(), cmap=\"jet\")\n",
    "    plt.axis(\"off\")\n",
    "    plt.title(\"Label\")\n",
    "    plt.subplot(1, 3, 2)\n",
    "    plt.imshow(input_image[0, 0, ...].detach().cpu(), cmap=\"gist_gray\")\n",
    "    plt.axis(\"off\")\n",
    "    plt.title(\"Input image\")\n",
    "    plt.subplot(1, 3, 3)\n",
    "    plt.imshow(output_image[0, 0, ...].detach().cpu(), cmap=\"gist_gray\")\n",
    "    plt.axis(\"off\")\n",
    "    plt.title(\"Output image\")\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a7e3bc0-16f8-4226-b417-f952c3791d9e",
   "metadata": {},
   "source": [
    "We define the KLD loss that we need to ensure that the latent space is Gaussian distributed [4].\n",
    "\n",
    "[4] Kingma, D. P., & Welling, M. (2014). Auto-Encoding Variational Bayes. CoRR, abs/1312.6."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5e46b6b5-23aa-4fd1-9d7b-ee5ea799d733",
   "metadata": {},
   "outputs": [],
   "source": [
    "class KLDLoss(torch.nn.Module):\n",
    "    \"\"\"\n",
    "    Computes the Kullback-Leibler divergence between a normal distribution with mean mu and variance logvar and\n",
    "     one with mean 0 and variance 1.\n",
    "    \"\"\"\n",
    "\n",
    "    def forward(self, mu, logvar):\n",
    "        return -0.5 * torch.sum(1 + logvar - mu.pow(2) - logvar.exp())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "519291dd-f634-44e6-b1b8-b2f3a5e2349b",
   "metadata": {},
   "source": [
    "The SPADE paper includes a feature loss which acts like a regulariser of the discriminator. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "7944e04c-0183-4976-98a5-da92979a7e4f",
   "metadata": {},
   "outputs": [],
   "source": [
    "def feature_loss(input_features_disc_fake, input_features_disc_real, lambda_feat, device):\n",
    "    criterion = torch.nn.L1Loss()\n",
    "    num_d = len(input_features_disc_fake)\n",
    "    gan_feat_loss = torch.zeros(1).to(device)\n",
    "    for i in range(num_d):  # for each discriminator\n",
    "        num_intermediate_outputs = len(input_features_disc_fake[i])\n",
    "        for j in range(num_intermediate_outputs):  # for each layer output\n",
    "            unweighted_loss = criterion(input_features_disc_fake[i][j], input_features_disc_real[i][j].detach())\n",
    "            gan_feat_loss += unweighted_loss * lambda_feat / num_d\n",
    "    return gan_feat_loss"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3419f8dd-f26c-4852-bc7d-2047ca3f6826",
   "metadata": {},
   "source": [
    "SPADE can be used as a GAN, for which only a decoder is necessary, or a VAE-GAN, which includes an image (\"style\") encoder. The decoder incorporates special normalisation blocks called \"SPADE\" blocks. They take the semantic map and obtain rich features to normalise the activations per semantic layer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "3962bd41-9c31-46c5-880b-f451e8576d2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "net = SPADENet(\n",
    "    spatial_dims=2,\n",
    "    in_channels=1,\n",
    "    out_channels=1,\n",
    "    label_nc=10,\n",
    "    input_shape=input_shape,\n",
    "    channels=[16, 32, 64],\n",
    "    z_dim=8,\n",
    "    is_vae=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16c95b4d-5d61-4054-8105-cf987fe55b82",
   "metadata": {},
   "source": [
    "SPADE is trained as a GAN network, and therefore, requires a discriminator. In Park's paper, a multi-scale patch-GAN discriminator is used."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "6dc243a9-10ab-4e97-9bbb-a6314fa1556d",
   "metadata": {},
   "outputs": [],
   "source": [
    "discriminator = MultiScalePatchDiscriminator(\n",
    "    num_d=2,\n",
    "    num_layers_d=3,\n",
    "    spatial_dims=2,\n",
    "    channels=8,\n",
    "    in_channels=11,\n",
    "    out_channels=11,\n",
    "    minimum_size_im=128,\n",
    "    norm=\"INSTANCE\",\n",
    "    kernel_size=3,\n",
    ")\n",
    "\n",
    "adversarial_loss = PatchAdversarialLoss(reduction=\"sum\", criterion=\"hinge\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d83908eb-df5b-45dc-a24d-8148f1d7ce19",
   "metadata": {},
   "source": [
    "Like in the paper, we also define a perceptual loss:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8823799d-4762-4884-bce8-ec1faa457d07",
   "metadata": {},
   "outputs": [],
   "source": [
    "perceptual_loss = PerceptualLoss(spatial_dims=2, network_type=\"vgg\", is_fake_3d=False, pretrained=True)\n",
    "perceptual_loss = perceptual_loss.to(device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "2df58c7a-de0f-45d0-b201-5a5e6bbf24e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "kld_loss = KLDLoss()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "8dc58031-feb2-48ce-94a7-6ac21b134d41",
   "metadata": {},
   "outputs": [],
   "source": [
    "optimizer_g = torch.optim.Adam(net.parameters(), lr=0.0002)\n",
    "optimizer_d = torch.optim.Adam(discriminator.parameters(), lr=0.0004)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2511adc2-593e-4c20-9a56-e366de82047c",
   "metadata": {},
   "source": [
    "## Training the network"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0033a3c-5aee-46f3-ac50-301546ab2783",
   "metadata": {},
   "source": [
    "We train the network on the following loss: a KLD loss to normalise the latent space, the adversarial multi-scale patch-GAN loss, the regularising feature loss and the perceptual loss. The training parameters have to be defined in the following box:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "d8b575ad-0993-4a90-8204-28d7354658fa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 0/100\n",
      "Train: kld: 466.404434 ;perceptual: 1.821399 ;generator: 16.703516 ;feature: 0.204867 ;discriminator: 1.062856 \n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x150 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation: kld: 49.194275 ;perceptual: 0.248631 ;generator: 2.829963 ;feature: 0.211503;discriminator: 2.083022 \n",
      "Epoch 10/100\n",
      "Train: kld: 549.825611 ;perceptual: 1.575798 ;generator: 18.242220 ;feature: 0.225069 ;discriminator: 0.804555 \n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x150 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation: kld: 79.829468 ;perceptual: 0.215445 ;generator: 3.057718 ;feature: 0.204359;discriminator: 1.654130 \n",
      "Epoch 20/100\n",
      "Train: kld: 393.733963 ;perceptual: 1.386193 ;generator: 19.034620 ;feature: 0.199388 ;discriminator: 0.725488 \n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x150 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation: kld: 52.229641 ;perceptual: 0.243125 ;generator: 3.204406 ;feature: 0.220542;discriminator: 1.396598 \n",
      "Epoch 30/100\n",
      "Train: kld: 751.861000 ;perceptual: 1.798046 ;generator: 18.385619 ;feature: 0.202928 ;discriminator: 0.797655 \n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x150 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation: kld: 122.499054 ;perceptual: 0.268300 ;generator: 2.987622 ;feature: 0.191174;discriminator: 1.627047 \n",
      "Epoch 40/100\n",
      "Train: kld: 1697.766708 ;perceptual: 1.966475 ;generator: 16.803330 ;feature: 0.148116 ;discriminator: 1.307467 \n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x150 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation: kld: 203.240021 ;perceptual: 0.321197 ;generator: 1.874963 ;feature: 0.101181;discriminator: 3.520483 \n",
      "Epoch 50/100\n",
      "Train: kld: 1747.244675 ;perceptual: 2.297118 ;generator: 10.888644 ;feature: 0.093298 ;discriminator: 1.565655 \n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x150 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation: kld: 142.216095 ;perceptual: 0.377798 ;generator: 2.002392 ;feature: 0.101893;discriminator: 2.888488 \n",
      "Epoch 60/100\n",
      "Train: kld: 1580.717529 ;perceptual: 1.940898 ;generator: 13.716251 ;feature: 0.098396 ;discriminator: 1.517600 \n"
     ]
    },
    {
     "data": {
      "image/png": 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BMQm8LVu2cOqpp3LCCSfwxhtvsHz5cs4++2zGjx+v1lm4cCG33norCxcuZPLkybzyyit88sknXa7npEmTALj22muZN28eNpuNU045RZFtb+NrX/saWVlZzJ8/nx/+8IdYLBaWLVvWZeC02+0sWrSIyy67jGOPPZa5c+dSUVHB0qVLGTZsWIxFet555/HEE09w0UUX8dJLL3H00UfT3t7Ohg0beOKJJ3j++eeZPHny/h3gfusE+gAiB+ruZ9u2bcbNN99slJaWGg6HwzjssMOMZ555plvJxu23327ceeedxpAhQwyHw2FMmzZNSUh0fPrpp8Z3vvMdo6CgwLDZbEZxcbFx8sknGytWrFDrDHZJVVpaWpd146U5B3rdli9fbpSVlRl2u92YMGGC8fzzzyeUAb3++uvGpEmTDLvdvk95VXeSqjFjxnRZt7S01DjppJO6LAeMSy65RP3f0NBgfPe73zVycnIMj8djzJo1y9iwYYNRWlraRYb0/vvvG9OmTTMcDodRUlJi3HLLLcZdd91lAMbu3bu7HOusWbOMjIwMw+l0GsOGDTMWLFhgrF69utvz++CDD4yzzjrLKCwsNGw2m1FQUGCcddZZxocffphw/f/85z/G2LFjDbvdbowcOdJYvnx5QknVhg0bjGOOOcZwuVwGoM5L1l2/fr0xZ84cIz093cjKyjIuvfRSo7m5OWYb4XDYOP/8842MjAwjPT3dmDt3rlFdXZ3wnt14441GcXGxkZKSsk951d7ez/jrCRh//etfY5YneqZfe+0148gjjzRcLpdRVFRkXHnllUpOF/+O3nXXXYozjjjiCOO1114zJk2aZJxwwgkx67W0tBi33XabMWbMGMPhcBhZWVnGpEmTjBtuuMEIBALdnl88BhSpJtG/6O5h/6rjRz/6keF0Oo22trb+PpQDhpBqTU1Nfx/KgEF7e7uRnZ1tLFy4sFe2P6hiqkkk0dtobm6O+b+uro5ly5YxderUHldQJNH7iEQiXcICf/7zn6mvr09YZt0TGJAx1SSS6C8cddRRzJgxg0MOOYSqqioefPBBGhsbu9UxJzGw8eabb3L55Zdz5pln4vP5eO+993jwwQcZO3YsZ555Zq/sM0mqSSSh4Zvf/CYrVqzgj3/8IxaLhYkTJ/Lggw9+KVsRfhUwdOhQhgwZwl133UV9fT3Z2dl85zvf4dZbb1XVmT0NixFvGyeRRBJJJPG5kYypJpFEEkn0IJKkmkQSSSTRg0iSahJJJJFED2K/E1UWy6JePIwk4mEYi77wNvq7Rvurhp5KT+Tk5NDa2kpHR4dqDmKYmvIu63Z3j+OXf1lTJ4nOf1/XKiUlBbfbjcPhwOFwJOz38EWQzP4nkcQAQ3t7uyLUjo6OvRLil5UsDxQ6uerXpLvrs6/r+kWQJNUkkhhgEEurO4trf9CdBXug29tfb6e/yH1fxyef69dSP9be8OaSpJpEEl8C7C85dOcu99b+e5NsB2p4K0mqSSQxwDCQrMkDieP2plXdkwTa21Z1klSTSGKAQXdVdfd1b+v3ZWKqp7cdf66C/SHS/TmWRDHW3rw+SUlVEkl8yTBYk1e9fdx9dV2SlmoSSQxg7C8RDFYijUciq1uWDxYkSTWJJL6i6M7tTrSOju7kS/HrdDc55IGit8INvYUkqSaRxFcYiQhVj+PurbhA/zyeqGT5V6UIQUeSVJNIYoChr6RCeoVRSkoKFotF/daPYW/ZecMwuhQq6NvRtyef6+vr25J99STx9geJJ0k1iX7H/mS4k/jiSCRREuJLTU1Vv1NTU7tYmvpvfTttbW20t7fT1tamSmstFgtWqzVmeykpKXR0dKj12traEhY47E9IoifRG8/cl4RUz4CcQ6F2UX8fSBLsiaelpqZitVpxOBw4nU4Mw6C1tRW73Y7H41FWjM1mo6Ojg+3btxMKhRI+6FarFZvNBphlnFLKmcT+I5FkSQjQZrORmpqq6uFTU1Nj1pF7pX9X7mdLSwstLS00NTWpKbuFTN1uN06nU21P1mtubqalpSXGwo0n14Eq7t8XBiepjl0EM4HFrUAruUYtNQcDnkVcueUGXmUab1he2csGDoFzvw2jgOuWAq1A5V7WT2J/YLFYcDqdZGZm4vP58Pl8uN1ucnJyyMnJASAcDuN0OsnIyCA1NVW9SH6/n3feeYe1a9d2IVaLxUJeXh6jR4/G7XYTCASorq5m586dNDU10d7e3i/nO1gQb/0JkcqgZ7fbcTqdOBwOioqKKC0txeVyKatTSNZms3UhunA4TCAQoKKigoqKClpaWjAMQ23f5/MxduxYsrOzaWtrw+/3s2nTJmpqamhubiYajapBUgbKRBZsbxDsV7j23wZMhwVTYQ6wGGyPNdK624sx346l3aD6pFL4MVjnhbjt2kWQBguM3/OwpRh4r+v21n0b418WqAMLLcCzwCHAZqCi707tSwS73U5BQQFlZWWMGDGCIUOG4PF4SE1NxePx4PV6aW9vp7m5mVAoRH19PSkppky6tbUVp9PJhAkTsFqt1NTUEIlEiEQi6iUdNWoU3/jGN/D5fDQ3N+P3+9m2bRsffvghW7ZsobGxMeEkb4MdPR1jFKtTyFSsU6/XS3Z2NuXl5ZSVlSmL1Wazqd92ux2bzUZ7e7s6ppaWFmpra0lLS8Pv9xMOh2lvb1fbzcvLY+zYseTn59Pa2kpdXR2pqam4XC7q6uoIBAK0traqHwknxBNrT4UF+uL5GASkWgrrppp/bgY80Pqcl2vO+QVcCwYWmABUQ/tdHnO9sbCLIuBUupIq2Aoa4d9gfAh/Mc7k7O8+BVcAc6bChkV9cE5fLthsNrKzsykrK2Ps2LGUlpaSmZmJYRi0t7cr97+5uRnDMAgGg/j9flJSUtSLY7fbycnJYfz48QQCAZqbmwmHw8qaKSgowOFwYLFYFAGUlJSQmZmJ1+ulsrKSnTt30tjYmLRc9wKdVG02G263G4/HQ0lJCVOmTCE/P1/FVLOzs8nKysJqtcaECSTZBKab39zcjM/no66uju3bt9Pc3Izb7SY7O5tRo0YxdOhQvF4vFouFgoICfD4f5eXlVFRU8MEHH9DU1BQziAq5dhd3HegY4KS6CG7t/HMOsKEOfuyDq2HyOashAwgk+NoGeD51NtyW4LMMsORci2WegbHQQhZ+WFoFS/OBHcBETCKeAbwFtGGGB5JIBKfTSVlZGSNHjqSoqIghQ4aQm5uL1WolHA6TmpqK0+mkvb2d1tZWmpubCQQCMdnf1NRUMjIyyMrKYsiQIcAei6Kjo4NIJEIgEMBut6vkh8vlIjs7G4/HQ3l5OdXV1WzcuJHVq1dTVVVFU1OTeikFg+nFFPTEMYtHoMdO7XY7breb8vJyxo4dS3FxMcXFxcpSlMRSMBiko6NDbUMGQrEm7XY7HR0duFwuJk+ezPjx4+no6MBms2G1WklLSyM1NZVwOKxce5vNhs/nIy0tjcLCQgzDIBQKUVlZybZt26ivrycSiai4qyTCEpHr57Fce5ukByipTgHSgZVQMsNctAF2GCMosbzKycZHfOtv/+bdK0cz8dqPu359G6y6Cl7oZuu/w8Jpj+ZiGWJgXGXhVeObfMxoLihbDmPB0mDAGiCUDZmHgn8V8DHJuOseWK1W0tPTKSsrY+rUqeTm5pKSkoLdblfJKbFSXS6XcuPFCpUXVawlr9dLeno6drtdyW9E6tPe3k5WVpbar7itNpsNp9OJz+cjOzuboqIiCgsLqampYdeuXVRVVamQQCQSUf9/1aAnm3RSTUtLY8iQIRQVFVFQUIDL5SIajdLc3KzW7+jooKWlBSAmWSWDoliwdrudoUOH0tHR0SWJKN/Xv5OWlobL5cLn8+FwOGhtbVUD8u7du6mvr2fr1q2KWHUpFvRcc5jewAAl1WzgCEi1wLmYVipQ8qs6uAkuZyEvzDwOH7UJv+373Q62/O5gXkhNbGHWAw9Zakwr+Dcw7R/vwmJYGFgOr8GLdV/jOMvNQDFkAn6Ao4EnevIkBy3EBS8tLWXEiBEUFhbicrlobW1VD67ValWWkbiPbW1tKgSgv+iS1NA1jfK3JDCsViuAslQl1igSHYvFgt1up7CwkNzcXPLz89m2bZtKZIXDYQzDYOfOnbS1tfXn5etTyLWU6yak6nQ6yc/Pp6CggPT0dGw2G2lpaQAxcVGbzaYSh5LYEmtVINuU0IB4JSkpKco7ibdwJU6bmppKdnY2brebIUOGUF5ergj1P//5D3V1dere6eQs97+vJVj7gwFGqjYouBbuAZxAKuTO2kZL1E5gYQF4YPHRF3Ls8jdoHuuD1Ym3Uj+7mPuevhBzQ3vBKLC83YLxJwuUgPGBuXg068EzA0J3QdtwmDm10+xdBPwTM5nVBjR+8VMeZLBarRQVFTF58mRGjBhBbm4u2dnZtLS0KEtIT3C4XC4lpwkEAoTD4RixOezpdK/rG8UqEddP/hdLWDLRbW1tyvpMSUkhKysLi8VCeno6mZmZtLW10dLSQiQSoaCggDfeeIMdO3Z8KYlVJ5hECSmn00lWVpYKmRx33HF4PB5aWlqUhwAmSeqDWjQaVddatg/EEGlHRwetra0qni0E2tHRoQZNucf6QJiamkokElHE6fF41D5mz55Ne3s7mzdv5vXXX6exsZGmpiai0WhM5/4DKbf9CiWqxkHBtyAHeCz2k5FsxO/IJFBSgK2gkSJ2Qh3w1+63ZpRaWGXp3v0XvDrbwrTrDFbdOJGjfXsSWvm+AIbbQmbtLgKjMK/S4s7fnApvAiuBHX8DPjywUx3kSE9PZ+LEiUyZMoWsrCzcbreySJxOJy6XC5fLBaBeZMkYS5xTXlh58VpaWpS0RkhVQgBCDi0tLTFyLLFyhIAl1OBwOJSVLMci7n92drZKflVXVw/KGOv+QohVTzA5nU4lb/L5fGRmZirXurm5WV1P0Q0LQco9AJT7rZepyiAp90IkVfpvsVzF45BrL+EdiZfLsbpcLsrLy4lEIrhcLhoaGqioqGDXrl3KEj4QZURfWrIDhFSPNxkwBEQwrVTMv4OkEyTdNAz3F6lwiBVea4fmblbJB4oBHoBpK97FOMSCoYVnjTbwv1mIBQPuwCT7UXDUOf/jDeexsHwTEDyw0xzksNls5OfnU1hYqETdTqczxuqw2WwxbqC8bPr/8Q05xLXTLR2BXuIYiUS6lFbqL6q8+FJQ4HK5VKJEtj9kyBC2b9+O3+8nGo320ZXre8Rbqw6HA4/Hw6GHHorP58NmsymLT6xRsWjFepQBUK4rdLX4xBqV0IAe95T7olumTqdTrSf3VaxZp9OpvA6Px6O0szabjSOPPBKgi6Ua33+gP2YgiMcA6KdqgxO85p8nA5PDZhIe4AFYO/xItlpGwhxovc/Laibve5NnQU6uQYExF1c3q6w3bqPED+xelHBosaSCZYZhyrVCwH1Qds5HXMZdXHP+L6BiKLAAM9bq3c9zHbxwOp2MHDmSY445hiFDhiiLQnf3JVElL4NYKfGWp+6uyQsbDofx+/0Eg0FFrkLEEgKQTLC4k4B6GdPS0nA4HDEub3p6Ol6vF6/XS2ZmJtnZ2YwYMYLjjz+esWPH4nA4+u167g2fV0akE6ncB7kXJSUlHHfccRxyyCFkZGRgtVppamqipqaG2tpaIpFIjE40EokQjUbVvZDKqdbWVpWZD4VC1NbW0tDQEJN81K1a+Z5ss6GhQVVeRaNRmpqaaGpqorGxkcbGRsLhsDoGGZxbWlooKSlhxowZHHXUUWRlZcUkNfXrFl+hFf+jX9/ewgAg1VZ47m+wAibWrIKpbjghDCEoW/KRqR8tsMBTMPzatfw693pcC+r2bmP/E3bs8lHB0G5J9e6br+L4jGe5zmjBWBBrpSpkYlZdpQKPwa1cTSrtOIjCIhuwEu45Hqb+5Auc/8CHx+Nh7NixTJs2jbKyMtLS0lRW2DAMlckV6IQbb7VArGsqkO3Jyy0vhrx8HR0deDwecnJyFGGLVSuurbivdrsdl8sVQ+5iUaWlpTF27FhOOeUUJkyYoJIzXybEJwCdTidFRUXk5+cTDodpaWlR1qvL5cJisRCJRPD7/TQ2NtLS0qLCKxI+gMTWnoRvJImkJ7N0iAUMdAktyHKd2OW3HKfdbsfhcFBQUEBeXp4aRPVwUfwz1V/hnX4m1UWwdBHMNOOpRezizld/wHjjA/BAdVMeXA3GFRaMCy18Mm4CuTXb+FXGdaaBuBcUX1vP9eN+TX3c8vmY2oLfXAsv1Z/Ii8zEuDnBBo4DQmC7opFrJv2C6477PwA+YBw7KTKJds4Mk3QXA5mLPv9lGMCQEtFJkyZRWlqK2+1WZCnaQafTidvtBvZM/SvZZrEcRAXQnc5Qd+N1AbjuHmZmZpKZmanCCaI20F9kcf3lOGWfQtiwJy48ffp08vPzB1Tm+ItCb5AiVVB5eXkUFxfj9XoJhUK0tbUptYTL5cJut6ua/HA4TDQaVYoN6KpN1S09GQyj0WhMAlIvPdUJVD7TB1shVTku2XcoFKK1tVVZrCKfGz58OAUFBWRkZKiYfTyJd0eoX/JEVT4sxHSvVwEeeObBM6k738fayglwH4SeyiVlQxPG6D3fmsxqfmo5gqCRzvUv/7rbrdf8ysOyX51HtmVJDLFuNKbzw7kvQzVYTjJ46o1ZCb9vucqAd6B1lZdbCn7JX6bMBuCm226GAswY65GYUtobN7HD/8jnvxQDGE6nk9LSUuUyygOsvzASK5NkA9DFhZcXWJfj6LEwefH0OJy+Tmtrq7IqxR0VkhQLVT8mvVZdZD26iD09PZ1x48ZRWVmpChIikcigbNKiS9QkSSfuf1paGqeddhrDhg0jEolQXV0dc68cDgdut1u5+q2trYrkAHUNdb2qQK5lW1ubUggAKkYrlmdra6uKo+pxdrFe7Xa7GkAzMjJwOBwEg0Fqa2sJhULYbDbS09NVwYDD4WDo0KGsX7+eDz/8kKamJoLBYMz92x/y7C2C7T9Ltfxi+DFmYuqBLWY2fTdEsTO9eCXcB8duf4b2KzwxX/v3vd+CggUsevA2Xv7VEd1uPvd/IX56/O+pMa6JWT7M8jIcDJevvBk2wGn5/+n+GBdjxlNrob1z/DnxqidhMqYCYLF5zDtOGQ6XLgJcmL0KJjLY46wWiwWXy8WwYcMYP368qpyRl1ePd7W3t+NyuVSsy2q1xtRwt7W1qTJUPY6pk6q4/BJ7EzcV9mhTJbsciUQIhUJKxiUyKyFbCRfobqXIhkRobrVaKS8v54QTTuCb3/ymKtGMt3gGK0SeNHr0aIYNG6aSULqOVKqbRCUhA5N4CfEWr3gecl9lkBIiB2IGR9mfLvoXr0KOUY+3SzJLXH7xNITwOzo6SE9PV5V7hxxyCIceeii5ubkqIRmfCO0P9JOleiJ4MKuWJgCrDjYz/k74NFrOVY7b+HbrY/zgD0tNN/zfe75p/AL4IRhPWlh7/nDTl4/38QHqoO6/LrL/HuF+YChw/GTgdHjz/8az+N5rMJ6xYJy6l8NcBZwLU8f8F2t38oOFMHXKf5nMahZfeg3UYhLuFY8zmHWsVquVvLw8hg8fTlFRkdIRtrW1xTy8ElMTqZPu4uuZ+5SUFHJzc9m5c6fKusdna1tbWwmFQipJIRpXiZk6nU4VdpB4rlg9ehxOCF0vEACUUkE+93q9SnNbUFBANBqloaFhQFRdHahcSI+jSigkIyODUaNGKXdd5FJShCHXND09XW0rGo12Kc6Q+LioKATxhKqXlArx6iJ9/bnQSV28mmg0SjgcVtvOyMigvb0dv99PKBQiJSUFt9tNXl4egHoWDcNQUrkDSUL1Fvn207A8DtYsgXPfNQX8mZikWguBOQV8yDhyqDMrmRIlaDfD5f+6mQmnfAJnwF9/dXKXVT47s4ATeY4lp8/ngm/C8U/AkHc+wTLS4KiP1pjb/l33R7hjvA9uDcNjsOqs45Wl+uwfzqBszEemlRoBlsOq049nceE1Znz1amAFQNXnvDYDA+np6YwfP54RI0bgdDpV/1O9PRvscfWECPVmxxIbE2tFqrC8Xq9Kgug6R9FL6ttzu92kp6eTlpamLOBoNBrTi1NcU12OpSctRCEgiQ3Rs4pVK/Ha8vJyvN6B42Hs70sv56pL2mw2m0rstba2qiopSSiGw2FFYF6vVyWApLoqPtZtt9uVtSpWqPzIQNrc3Kyy+bI/ffCVAU8KNsLhMKFQSDVUkS5W9fX1tLe34/P5KCgowOPxqCY80WiUtLQ09dnBBx/M5MmTKSkpweVyxRQu6Ign2960ZvvBUp0Lj7lh6cXwXNwRZAKLDbOiCaAELE8aGKkWDM1QNM6yYBliwI5GGp+ycUH0fs5sK4TtmEQ3HMqu2k3tbTlcvO5h+D+w3GPADzu/P9MCUTBe7P4oi/PrYaYb5sGxY55RluqlF/6aQ/mQX9x/A7vvLIN77icjcgqBpwpgHiZZrwtjZtKe7okL1udISUlh2LBhTJ48maysLFXCGAqFFAmlpqYqa1DITG+64XA4YsID8jJIsqumpoZgMKisSNFRipvocrnweDwq7CCxuWg0qhJkOmHLfiWWKDHDlJQUpXkUi0iIo6amhpqaGqXRLCoqIicnh/r6+kFXcaWX9sp1kPJPabPocDhUbT/s0Y9Ktl+unW7ly7XVRf16G0CdfMU6lecgvopK1pNty75FCgeohJdY0Onp6QwZMkQVmDQ0NCjvRxqfp6enk52djcvlUtZqf6KPSdUGntHYZjaSPidI/ZxikwQFfuBSC2tencBINvKXc2Zz9j1PddmKcR4YqRb+ZJxFxkbTHbGcYV7IsVPeYd0/DodRYPzbgn1KgFabl7GPvsOH+WYM1vh3l0123UcbnP/fe/hz3Xco51NSMYnjGF4FYPfLZRzy0/f4+KkLCGwG5hnAy7AuDxgOlGCWFwy+Jiwul4uysjIyMjJiHvCUlBQaGhqUGwbmi5OWlqY0g/LCiFuolyW2t7fjdDrJy8sjPz9fWS06KeohAYmviruvJ78EujpA4oKS7JBtulwuFaaQUILf72f37t3U1dWpfYqec+fOnfj9/r696J8TutsvFqrdbqe0tJTy8nIyMjKora1VYRCJh8MeIpRQin5d5X8h2PhrLFaq3D/p+C/blXupq0F0z0IP0UjXMbfbrQZgv9+v+rxmZGTQ0dFBQ0ODSmAJZIAvKipi27ZtauDXy2V19LZGFfqcVNNx7qjn2oyb+fmJd5hx1QnA1TD+6TfZSRE1tx7Et3m88+C674tptMF3fY/yXR4FwDIOLG8ZrPMcjjHfgvE9MIAoGXu+cwBHakmFBy2X4vTXMzNBwesT00+hDStvvzqFxZWXw0VOuK8Vk1BTgTzMhNXgI1Vxr4TcxPXzeDyq3FAaUItrrbtc8SWSkpHXX17RHoolqpOrJENE/yjfj1cN6C6cWGeSTY63tIRMhAjEPYU9VUEtLS3qJW5sbBwUSoBEmlSXy8W4ceMYOXIkbrebzMxMldiTYg3YY0lKfDM+FqrrSWV9vZINUPFs3RKV33rhhoR75D7rPR3AVBlI2ay4+jJI+Hw+CgsLsVgsSqkh1rbI+crKyqitrWX37t0xna0Eici1t9CHpGpmxiNPZbN+/mimPvtfVp1+PKdNepR/TDiLK7iDdqyEj46T6/uBHwF37mPzH4NxrAWs0MmzXwhGGyw1vs2COx+Hn3b9vA0rZ699Ciash6ecZnHVY8eD/2/g/BZEGoFDzQNj8xc/oD6CNEwpKipSZCMvlsfjUbX+Yp0CMS+ZXtMtFlG8dErmKNKJWC9v1FUD8RpHSYoImQgh65VcQha6KyqIRCJKfuPxeLDZbASDQZqbm1VoYOjQodTV1REKhXrtOvcU4kXvbrebCRMmUFpaSiAQUPpO6Xsg5Ge321X8WOLMYo3q2XiBELdeWqq7+YlkdnJ8kkwSEpX7IrFY2ZdsNy0tTWXzm5qasFqteL1eNVWPFC9Iok0Sc4cccgjr1q1TSav+Qh+RqguYCwRhATya+T08M2vIeGw35/AXzrnxL2pNN+HYr94KllEGHXfuPbBstGFm3XsIllRYYHucia2rEn7egsNMVt06Gso7F64EFn3LLLe9wgt+A5NYBw+pyvQngBrtxWpzuVxkZGTgdrtjNKm6Vai777p0Ri8d1ElTEG8Vyff0THT8ZHSyDyFnebl1C1WX7bS2tiorR5+Q0Gazqb6rzc3N5ObmKqH8QEZ8csrhcJCZmUlpaSl+v19Vvsm9Et2q3itBj6eKtWuz2VRTabFixeUHYqxSCSnoJKrfNxmY9S5kumKgra1NVXZJeAGIid3q1XZATOMej8ejqvoMw6CwsJDq6mp1jfZmrfYW+ohUvcDBnX+/Bc9NIeTPhQXwgLGQhTzQ7TcXnXYViyy3kjLbwBhtMadB2dbzR2jJwAxFjAPLe4Yp8H8Grk44fQBYaaf0oQ1sfWuU2ewlAuR0Nl+ptYC/FfgAMwTwNINl9gCxBvTSP+kQBSgBfqLsqU6qegJDn+BPXq5E1TmwR2alW7wCPV4r1rGekdbLIxPVeQuhi7JAj/uKAN3v96ueAVVVVV2IfqBAt9yFCCWLn56erkInVqsVv98f08xbyDBeAiWDpVwTiWfLACU6UiFauY+6JlX3IOTa69VTugZVvi+JRdmO3GcZ8GSf8sx4PB6sVitut5u0tLQYK1eKAsRyFvRl8qoPSPUMs3v+1Z3/rphiEtACSNndhI+6vX57NOtZZpzJeS+vwLLAgMWw5rQRjM/fFKMI+CKwvAxnj32QRy3zoNUNV8Cy6XO616YCLdjZOmQUTMXsT3ATXPr07QDcs/lKOMEGL0yCtsHTXi4lJYWDDz6YCRMm4PV6YyxN6RQvmVo9i6sTpp58kBdfiE/WkUy+EJzuSuoljPKCCmQ/ktjQ69P1EIN8Vyd+IWNJuAFqG1arVelX5byHDRum5rwaqNDlaCkpKYwePZoZM2aQmZmpFAxyHaSqTEhSBPVinYMZGhFr1ul0Eo1GCYVCSuamJ5r0gUpCMPo90Ns2yj0S7bHb7Y7pBeHxeBSJi05WD+GIxSqDqLR5FHLdvn27ivUXFRWRkZFBXV1dl+l0+gq9T6pzDjV7OwumwlFH/w//Q5ncwPUxq7Zh7TyoWOvAQZQnpp/C5i3lXFd1ExPSP8HIsqDbSp+HYC2dZ2/ZakAU5hoPM8cUme4T6QS5Zvsv+JBxjGY9a56eoJQB6bNC3HLTL6FtB6YC4GjM2MDAhsViYciQIZSUlKiYqLyw6enpeDyemO5Tulsv0N3/+OSV/BZLMX6ZWDg6GeovqmxPn5s+XlyuS4vke7rwPTMzU2WZRRbU0dGher2KmiErKwuXyzUoSFUUDeXl5RQUFNDc3KySNR6PR03mJ3pTcd91DwL2SKwEqamp6npFo1ElZ9MLLfT4qB4fl+PTZ3UQcpSwC6D2JwOt7qlI7F3W15NabrdbNYORMIYQsh7j7w/0PqluoHO+J5h74cP8ve50dlLE7fwMgFeYpnSpP7AshXNh7rKHmcarVDCUkWwk05zPhHI281j+PObOeBpLbefDUAslmzax/e8jYA0Y+2j2L7CcCZZKw6yAmgOLmy80G2AfAA7jfQ7jfcDsSRCDocAqEZKXM1hIVbf8dMG8JKXEGpWXQJIb+gsqVml8ZY6+D6nMic/oJ3ohZB2Js4m1HO/ai8WrL9ctannJ5QUVd1SsML06Sz+mgQrdE8jPz1flmlK+C+Z1ycgwFTBireoWrn6u8damhBUkKSmNV+KnlIbY/rawpzmKkKbETfWyVBmc9RCDPG9Sjix6VmmsIvvQ47RyHuFwOGZQ7a/71/ukum4RlC/imim/4DDeZ45vjyX4EN/lWcsRcFGJmT2fACzfwRPLD+OFtpnUP1XM+d+6h7+3n05LxM5v0n5CJn6eePoUtY0PGMdNd96MxW/AAzC/bglTeIuLfA8nPByLE66ovJE7z7sOxsJfbpm9V+nW58EyzoPlfwOqgTMYLLMDCOFI4kPa58nDLy9DIBBQekCZCdVqtaqpiW02myJNPeapu4Oyvi670Ykv3qUXS0fcRonvJbJIdO2qWMECeeH0+KvE+STjLPsc6JIquT5Op5Pjjz+esrIyWlpa1LxP0kRGXGPpRJWamkp6ejput1uFYcS9FjITd1zWdblcOBwOIpFITKJR77kq91b6QkhiUGZs8Hq9OBwOpayQwVjuk7j0InuzWq2qB4S4/BIr1QsH9ASo6Gfjk6h9iV4m1YVwUwlshls2/JJz59/P09FTyHNU8SuuMy3Q+0rgPkxjbjkUjGlh98uHUn8fcCk86LnULGFdE8Ga1pX8DuVDnvjpKURx8MCNC/mUch62LOQHP15qyrHiwwJtgMXUwVLRyoccqqzNeLzCNO7515Wce9L9McuXr72A08Y/yjn8JeH35rCCxVwCPAKefAgV7+f16l84HA6ys7NVVU1TUxMdHR3KepBpUUKhEPX19VgsFpV9DQQCqjJJmg5LeWu8BSsvksPhUJZPKBSKaUunhxh0F0+2oUu2YI/VJi+bEL684HpfTt0Kkxc7LS2NvLw8wuGwssrjuzINFOihFxmMpEyzsbGRYDCIYRiqw7+uLw4EAsobkcFMXHK5ZmKZSrmpTPynt3HUu/K3tLQoi1WPmYfDYaqrq2lsbCQ1NVWFVPTiA+mDq2uThVD150efVFL2FYlE1HMiRColzPtDpL1Ftr1MqiUwu/PPNlj+0QV4htbgcLTwCtN4tPJss8t/LWbyytPKZN5l5eR0omMdXH7Jb1nPaJ5Zeybji9dgp/uH3EGUS7gXgIXGA7zATJZffIHZW6AWc64+lYGfa575RTbWPDshIak+wtkm6XvM445BCF5smsm4tA/5lHKGsZlPGMls/s7vuYTT+TtjjY2EOYbP3gUmv/U5r1/fQhJAgCr3i3eLdcITy6Sjo0O5lRaLRb2IFotZbqq3fIOuU6FI5ldim3qIQRJf4qrLdoQs47P8LS0tqp5cb1WYmpqK1+tV8hyxsOW7YGo8pehBzmugIZGaQUpP7XY7Pp+PpqYmAGWtyz2Usk69q1d8+z0ZbCSZlJqaGtO9H2KnR9Flbjox6pP5yf0SxYEkreT4JS4vJB//fAgRixpBBgUJOUmsVk+A9UeCStDLpPpPmHyq2Te1DVgAofJc1s3JZd3Jh8MJi2DGItPtzwEqbDwz50yzJaATfj35/+ABG8yDtZcfyW9/+2P8ZHGrkhIkhpswx/AK6UuChHHxLpNZd9vh4N9j2TAVvnXScmZ0E+t8tf0Y6jcUm6R8QtyH6yD0TC43rbjZbAN4NTChiqhhZ9Xzx7Nx1khqLO3w44PNsMYBTbDVf2hvbycQCBAMBlXnKV332djYqGJrIhYHVPJCr9PX467yAsvLLT075aURKzIzM1NNda27lrBHjyrWpa5AkHigPuWH/K+//GKliiUn8hzZjxC8ngQbyBDLsbm5mddff52ysjI1WV5DQ0PMXE5y/unp6Sr7r8uhwAwjyLW0Wq1Kk+z3+2MSiGJNGoYRM1uu3CvdgpZ5wkQzK4Qv1mpzc7OyQnX9arxlbLfb1X3Sm5CLflqel4yMDPUc6sTal2GAXibV9yDyHtyTDUN/COeiulERwSTUlXWw2mcub8MkqJLOr++2mZIlgJPhvQenQgU8dON31R4+ZBw7PhrOE2P2xFkBMvHzdV4CYCYvErzKozpNgWnZegh2G0+tX1FsknuiKVmnYupRNwNLO5edkM8/Xj4LroaakoPgmc5znQOmVvXZfVyr/kdTUxNvvfUWqamplJSYN0GsPbFAo9GoqkTSJTDyI1nn9vZ2Zb1KkwxdS6rXqktMTawSh8OhOirpvTuFBPT2ghBbpy4vs7iM8r/sr7W1NWYeLHElxbqyWCwEg0Hq6+tjMuEDDXqGPRAIsHLlSmpqajj33HMZP348Q4YMobq6mkAg0EUhIfdRBiTdGwiFQkQiERW+cTqdMR6KEJxudcpn0rgmKytLKSvEw2lublYNdCR+LQNYMBiM0UHLwCqKjFAoRFpamrJ+5XxkNl8Z1IPBIIFAQKlL9B4AidBbg2Yfif/roWIHXF1iVhtdhEmeM4B7fLAO0yLc3bn8HkzSvQKTaBd3/r4IOBKe/eiMPZv2Q8bk3VwQvZ97HJea80fFwUE04XLB1dzKHFbEVHMt+vZVLGrThP9rMI9zVOfvWzuP6SlgLKa1vQNYjtn6L1P7GQSZfzAtzq1bt+Lz+WLcPnHthKT05sN63FFeHr2BipCbnpTQ47PiouoyKNijEtBLUfVSViFReakTSbzkb/ktSZZIJKKSMLrrK6GH+vp6du3aNWBjqokQDAbZunUrzz//PB0dHQwfPhyn00kwGFTXUNrySZs9iY2mpKQQiUSUVyIDoYRSxLsAlBUv0Ke00ROJuocjz4+4/NL6T8IAUuUl+5Sm4jIgSFxYQgu6B5Kdna1CBhK60gtL+gN9WPv/gNn0edU5kDMcnlkFQzvN0DV0EukH8ONDTUtWKgT9wAPLgXNNUo1HGwSeKTDJbsyBH9X13MBnlhp+veF6PCU1AEQjnU1ca83t48fs/Uo+ZJaAfxNMHm5evTc3gWc4hHbA5M5BY1Hnxj1A6Fm6nyh74CEUCvHBBx9QXV2tGlmMHTuWnJwcRajx5ahiKcgLo/8WUtWzvCJpEgsSiCHCeIKF2PmN9OyvTqzi1ibSUuryL0mICVmI2ys9WvVM80BFvDvb0dGB3+/n7bffpqmpibPPPpvS0lLVPEXi3GK9ybWUkIh4HOI9iPxKvAO531IBJeQaP8ODeDXxsi4R7kv4RYhRVAdSGltfX6+IPxwOqyYx8ndqaqoKa4glLecv1rKEm/oLfd/6L3V4Z2f8qaYBdzIwFGw7GmnNaTWt0g3sIdWhwI/PhcWN0BbXQLhzbitWYSaiPgepWmkHzwyohdDqXPOKLMd032d2/o4ABIGSzoTacFj9X5hwvLmR0H/huuP3HNMDmOexbkvnRqo6D3Dgo729nbq6OmXVSSxMLAGxUsRNlxdNXhRx+cRt1IXheo2+Xm+eiFj1F0NXAAjpiZWsVwkJ2YplK7XiIuvSdZhSkinLROFQX1+PzWZjxIgRrFu3jrq6vVf89Qb25pbGfyZJOLm2kUiEjRs38o9//IPp06czfPhwLBYLTU1NtLe3x7jZbrdbyazkmomsSRCf8ZfKOrnP4jnIPYvvQ6snC6V0tqmpSXXN0pNVcs+EWGUWWOmrGgwG6ejooKioKEY7W1tbG/Os6P0Guour9ma8vI9JNdVMWh0JF8//Dc8zi8+eHwOT4Vrfr/hV7bWU+97j448mxn5tIbAwQUd2J5x2zqP4z8lSmf8DxS/4Ja8Ep3HPpz+D5RaTRHcAVMELedqa0wGL6fZnAiuPN/ly3XDYPdxsUN0GnACLjr6KRZm3wR0Hw5sG5ord9zcYaEhJMac+GT9+PKWlpRQWFpKVlaVcxba2NvWCiavY1NSkhOh6ggtiq6lEEaAnhGBPUYFuHer12/EFBLqoX09M6S9oS0sLLpdLNaUWa1lIX5piS2xOyjLFZdZLKQci9MKK1NTUmHaKUq4pkiepIpNYtQxoEqPUE5B6b9ympibVmFzq7d1ud0wDHH02UxnUgJi+AiK/km2Hw2Hq6upi9Mwir5I2fzk5Oao7lR6jlf4TUllntVqJRCI0Nzer8lz9+ehr9BGp2jDLNVtNgrwOllzxEzMJNKoVHrMxetJ67vNdxLXcZMYoJ2NqVzfDie88aVqUndhJIe9ZmoGj+dr81zn4C1qB9/zhSrgJMy5ajsmB5O9ZIQSsWAIMhfITTet5cudnEzDPY2xnIurSExl99HpKvrWJHXNWYiap4toZDmCkpKSQk5PDmDFjKCkpUdpCvZpJLFe905CItKVYQKxYPd4JqBimPvWKQE+m6ISsS4hkmcRo4/Wm8hLLZ9J0Qy+XFNcxLS2NlJQUNUtnMBjE4/EQCoW6WDkDFXIfRDImJFRYWIjVaqW2tlYpGcQKFRdZzlMsfRl8AOWqSyhFiFvKQyU2DahrLZ6CXsShx8ElNpqenk59fb0KJcnzICQp5yGTSIoiQZqmi0ck+xayjUajymMSfAnF/4I8OGGBGaNMxcycj30cHvs2T9xyBlxlrnV+5Z/gSCfwFkSmmJbfbKgiL6ZbVC0+fnDpUr5x9z+6JVQ/maxmMmHcMcuHsJ1xfBCT9f/LhbM5e+hTFMz6TC1rJ5Wayw8yB4EQ8MLFZuJsKGbYYioUjDfX3z3WAhedCE548LdnA7DjzuHAI5hNqssZLEhLS2PKlCl8/etfVw+uLugWghLXrbW1lfr6eoLBIGDG7qQySc/sy4sW3wRFTySJ9aM3WtGhW0cpKSmKuKUGXCwgqSSSeJzMr6WHHmT217S0NAoLC1WlTzAYVAmTgZz91y1UIaXDDjuMqVOnYrFYSE9Pp6qqSjVL8Xg8+Hw+fD4fdrudcDis4tKSZRdLVUI6NptNVcvJ4CQSqZSUlJhm0HoCUGLoMiCLByHVWaIpDYfDeL1e0tLSCIfD+P1+ldX3er2qYbVYulLeLHFz8TzkPotFq2tf+wO9T6o5i0zPNwcz/pmKSZYrv825081KpTBu7ERht9MsFpgwxfzuUmAzNMcRYw51PHF3rIQKzIYsIpt6ja/x8MUXE1+Sz63w4HFnq0IC6UQ1fdZznMo/Y1b96cLfm39I3FbCRRPg3PH3q6KBfxqncolMgNWJP/70PC5ZcC+t93hh0d/2doUGFNLS0jjooIMoKCiIkd+IuyiWpVgg4XCYSCSi+llK3Az2THWh60p1t0xeRhGw6/PEC3nGl6zKMkl8CEHr9eAiF9I7LumSIKlD93q9ZGZm4vV6SUlJUcRhs9lUXLk/sL9koFv00oFLjl8IT+6dyN0cDkcXTa+QMphVSkJMcv+kObk+yMq9a2xsVJP1yTWTKrySkhJ8Pp+6N16vF5/Ph8vlorCwUDUFl8HT7/fT0tJCQ0ODipfLcUiMXpJpck+FyIPBoNJXy7VJZKX2hfa490l1BqaF+gKwHFI2NNExOQ0mwKnT/0mQdM6/+C9MXfJfM7u/tPN7qzAJcRWkPxRkIyMZycaEuwiSzhaGsrjpckLP5JoLN3RuKxL3gF5h4fwr/mKeuRO+cdo/OI4XuJD7YqzXNqzgNGC1ZY+M6mqYuH0V762dShAPQ9gOkDCem4mf7/j+zIPPXIoZAhj49f8WiwW3261ceIm9SUs4WS4uo96bVEpbw+EwTU1NpKenx0yzohMqoMpdGxoalIZRLEx5ESQrrFdeScciXXIVH1uUY9RjhPKZfEdigxLOkJdQYrySAOtP7G+ppciWJGaZmpqqyNEwDGVtCgnKOerqCb1MVZKAMgjJfZcWibW1tTQ2Nqpy5draWkWqYjnLvQ8EAuoa5+TkAKh+vbq8TgYEIUnY03tXnp1E2mTYE3uXFoWyTPeQ4kNIvYm+cf+fgdK/b8B/RyY/cPyeh7YviG3+vBtW/er4PYQKpsD+amARvD1tOoWv7kxIqmHc/IELefvy6WbWvnYfF22NYRYhAGDhP0eexn/uO42l479NavysA89YYAVkr6ykfl4xBds/4zss4+rxiRtXJzo223ONtOZU73vlAQR5gMVN0wlL/tZfZllH4mkS29KzyLDHSohGo+zatYstW7awa9cupUsUi0VvFafrHt1uN16vl+zsbNX3VLeegZiptMVS1YlZd/+FJMTtFLdVBoj+jKnua9+6UkIGBRkopGRVsuaFhYXqPEWAL0Sjn6eUsUrfBwmt6J81NjZSWVnJxo0b2bVrV4zbbxgG2dnZKjMfCASora1Vz4xYnkL4UkCSlZVFeno6OTk5hMNhdYwSKhKZljx/urJDwhEyO4WoGyRBJ+TbXWy1NyzX3ifVFY/D4m+z9d5RfOOSf3BL7i/hOXhg0kLWvXU4f5kyG+6JwFNOho9Zy6YTx5sxVzCrkcqByfA1Xk+4+QdYyNvHT++sfEr0IFYAr9FtsujNZth8Ltbxsbq2VNr544/OY/OPyhnKFj79uJwp7L2GP4ybBZc/DpPh0nN+zen8nUyfnyVk7/V7AwWGYagmGiKzSUtLIz09XVUiyYsqchwhPhFzi25Q4pKik9Qt1MrKStasWUNlZaXqMSAx0rS0NDwej3LbddlOohaE8eEBmWZDj+HqnankeGWOeglZAGqfXq+33zLHB4L4SjKLxUJaWpqKX+oz0EqCSgoAmpqalKWqx0QlPJKenh7TcLy1tZWqqiq2bt3Kxx9/zK5duwiHw2RmZuLxeMjLyyM3N5eSkhLS09OVKkRPLoqXIaQtOuWmpiY1GEo1lv5sAao4wePxKMtbkmiSpNNDOV/umCofm4mdefCfy04zq402wDrn4Vw55QZSaeeJ4jNpu8TKLor46eTfm677qM6vT4DckYnnT2nDyqqXj4cXEl28akxtVDUwETyjEx9eaAsZJ+9OWHGViV/1Sc3pZoaCB1jIOD7ERx3tWDuVA/D7qks4Jv9VljWdR4/MRNhHkI5RUjooYnG91RqgLD29k7yuCIjP4ssySWzV1dWp2KfEzDIzM8nOziYzM1MRnN6tSqBXYOmEKr/jQw76/2JJSyxYSFXWk56fAz37r4vxW1tbiUajVFdXU1lZGUOEwWCQuro6Ojo6yMzMVNI4p9NJJBLB5XKp+nsZqCTbr4v2dR2p1WqlsLAQm81Gbm4uPp9P3TvJ2OvSKr0XgO5VyP70QgRA/Y4fMCVkJOEdvYev3N/4yrv+QN+4/0/dD6sugNp/wgOnmgmfB+DXG64HP/zx/PPIxI+LsMmDo2D8mD2z+K19+Uiemn46l/PbbnagmfBDMZuY3JcPuzu1ofNOJGPp7m6+6+JCxx8O+JSCpHP+w3+BZ+A/l55GxpG7iUbscPImYDgdd6QR/amD0Am5QP0Bb7+/EIlEqK2tVUkj6YAk7rR0ldenIhFiFJ2pWEe6lSgkJS3oRL4j5JmRkYHX61WifHEP5YWKrx7SK7qALn/Hx3HlGKSySDoetba2KivI6XSSnp5OTU0NtbW1A5ZU9figEFY0GmX9+vXk5uZSWlqKy+VS+mG5jykpKeTn56uYp4RdgsEgjY2NSu0g8dT4EIyEgwoLC/F6veTm5pKTk4PP5yMjIwOHw6EGX739niQ8daWAXo0nLr1MyCjd0uSeASp8ILFu8WqkqEDuZUNDQ8JpVPryXvaRpKqtM9Z5Ymd10ltw0xRTRF8B369YxhM3nkIOdTz40Nm0Y8WllXY2T3fF6FT3HHw735q+nOdDs9Sy0WnrOY9lcD2EO13+LM5Tswf0FOy0MHz+WjatGA+zIbCqoPPcss1JA69o5Lwr/gD8pkf329uQF9Rut6tSRSExiXtGo1Hy8vLUQy1li7roW0gVYrPFbW1tZGdnM27cOEWuoiwQS2Zvrnd8VUx8gYFeUhn/mcQV5aWUl1mOORgMYrFYeO2119i2rRdml+wlyLnu2rWLd999lyFDhsR4DJKh37ZtG0VFReTm5pKdna0IUwY3vYhCBP9itWdkZJCfn89BBx2k+qtKKEi6RekNpXUrVf4XHbHsI35g1O+/xLZFfyrTa3d0dBAKhVRbwYyMDKLRKA0NDWzfvp3NmzerasD+8jb6iFQbMVs6tcKo0UDn5H9DgeVw/sg9c6CkE+zy7b01Q/k2j/PttMd7+Hi7x9xP/8k1w66nBTubbhvP8KfXsuma8Waj7YswVQIAIa/Z5erNYszzHxwwDEO5xZIJFmG3EKPe+k2v79aJLd7C1DWm+rzuYo2KFla+o1uj8S8exFZpxR+/JNDkeOUF1gsDRMCu16R3dHRQVVXFp59+2q/zxu8L8ddDrq2Uf0pcWpciiYXe2Nio3GSpbhKPQp+mRm90I0QoMXaJv0ovAblHeqNquX/6/dC3DXv66uqSO6mQkoFZ9i0DvTStFitbKqmkKbaEq/bX/e8N0u27iirPcAhtMcs8F4BtcyNDfNvJp4oHb7uUWVc93zeH8jnQhpVruJWtr5mzp95RewWtu72QA5uOHw8vrIR1M0z52MmYFniEznLXPq4E/oKQTlXbt29n6NChKusu8iSZYkUaAsfLVeJfeHH19CqbeCkU7Gllp7+IkJg0uyNUgcTaJHQhAnJ5WR0OhyrbFBdZulTt2LGDzZs392tDjgOBTloiipeCB3HXXS4XgUCAmpoaGhsbCQQCqpGMfk/1LmIiP5P4qLjmOvGK9Sj3VR9gdUsV9kxPLevoJcDyfbGagZg+BRLi0GccaGhoUC0KRdOqT6mdSJ8aH9/vLfSdpZoDrDrY1J6Www2+6xnKFgAuu+quvjmMzwk/meZ01AuANZiEegJm39c3gYIZJonWAktlBlWA9xgM+lQdhmFQVVXFxo0bOeigg1TjlJycHFVLLi6hvFDxpaZATLJHiDCeSHVrVhfwxxOnHpNNFGMV6NpHEZEHAgElSBdrVfSp0v1IiCYUCrFt27YBHU9NBBm8xIsIh8MUFBSoblNSSZWbm0tdXR21tbWqOYkQskjiZDv6fRUVQTAYVEkrvRoufv34wU4SUXrXfzk2cdXF3Zfy2cbGxpiGPKJDbWtrU+oCUXH4/X52796tEnJ7Q1+I//uut1nFSjgSM0nlgf/7+W95mynq53W+xtzHn+6zwxG0YWXuu0/zS37BD/ldwnXSCTF++5tm05RU9UV4c5VZ+38Ppvb1AeBk6bDdjEmqgw9tbW1UVVVRU1OjrBEhGYm3idslL0W8m97d//pPvEIgUUYfYoXesKdsVlrAJdqHCNgTzZQqkiKR+UhMNxKJKCtuICP+GunSKr/fz5o1awiHw6phTE1NDVVVVarAQqaT0S1UPXSjFxHoFqtetaY3r0l0XKJrFomWFJUAKuySkZFBZmamakou56GHHSQMJRa3qE/EItVjr1JR1Z21Gn+cvYU+9E1XmrMA8BNTOroyzOIFndOi+M0TtM3s+9jj9dwAk3ew7o7D4YqV3GtcwmRWx2hSg3hYm3WkGTOVwoH7gNn5avpt7sB0+5/ZgtmM5W4GUx9VHR0dHXz22We8/fbbjBgxgtGjR+N0OlX7OP1F06cN1rO1gn1ZqPHQY2/657o1rDfOEF2qVE3JNux2u5oIT1xHKUMNBoNKG2m1WvF6vbS3t7Njxw527NgxoOOpgkRhl44Oc8qbd999lylTplBUVITb7aa6ulqRlljtQnbxEjjZtiwTBYA+AAqxJgrR6KSqa4P1MthQKBRD6rrFLBVZdrtdTXsjRRx6rFWvnopEIuzevZvq6moVU+1PT6OPA36NcNFKmDwDlrpNl3kxprXngVanF3x9e0TfZSm3Ra4iMBMYNYOXX4aXZxzDWcZjnM7fAVOjOrfhYZ44Zb7p4q+ms/qrGQjD1W4zHHAkmNapl8FKqIJgMMj7779PMBgkLy9PudViFeit+ySGKS+ckJtOhEIC3ZUP6khkyerLJFMfDAZjigXkGCXJ4vP5aG1tpbq6WgnbRU/Z0tJCY2OjiqkGAgE+/fRTduzYMag6/gvkOjY3N/PJJ5/w4osvUlhYSH5+Pi0tLdTV1Sn3WS/7TdRyUfcchBT1658IiTwT2YZURol2VQY6wzDnCBNtsC6xa21tpbGxUU3gWFJSgtPpJBQKUVtbSyAQUFNdy0BSWVkZQ6rxMf6+Qj9kUVbC6nEo9rwIzp90D3lUdztVdG+hDSvV5Jn60ggmMTqBpe4uKoQJrOHvS0+ndYO3UzoF3HQo2VdXUr/SbXazWg5m5cLAdh/3B+3t7TQ0NLBlyxa2bdumKlmkubFe/gmxCQnoSow69GyxnqCKj/HJ8u5UAKK9FEtIn3xQMsnZ2dk0NTURDAZpaGjA4XCQl5dHR0cHO3fuVC/ujh072LJli5qYbjBAH5xgj3QtGAzy2muv0dzczLe+9S3y8/PJyMhQJGaxxM5yIK6+JKIA1e3LMPbMvqp3xdJ7peqWKRDzd3zcXBJjHR3m9C4ZGRlkZWWpQhIR/mdmZqpElXguNpsNn89HS0sLVVVVfPLJJ2zYsIFAIEBVVZVKWsU/Q/HXqbfRT/NF3L2nZ/MCeNByKX5zMideYRov8XVe52u8wEzu5RK2M4T7uLBLG78viu0MYXH6NUTuyTY7US1eCesg+9xKhlLBTop4hLPZTDmvMs1MUP0Ycy6tTOC6KuqXF8PMLWZIo+1+vgyEKpAXtKKigsbGRvVQ6uJuiV1K2aMI/KV4QCdNIMba1C2KePcykUUkn4l0R7SzkkjRhfASC5b+nE6nU+kZm5qaaG5uprGxkW3btvHuu+/y3nvvDboEVTz0gam6upp169bx2muvqeIK0RT7fD7y8vLUgCjkKNajrgiID+nIgNVdgx39/iX60SuohLhFHiUx8NTUVLKzs1VrRr3Llt/vVzrVuro6Kisr2bVrl2rZqIckEoWc4v/uDfSf3mf5DoiUwKXAm7Ce0QxhO/fYrjRlV/MicI8Tbl3PeuNqalwHsau5iCiOLlNUX88NuAjz3kdTu8yqujfkU83Y4DusW3t4Z4vAibAK6q8r5o4dV5BvreLjwyfy6pvHEPSn88SYU3jone+aEw8+BqzK7pw362kGU9XUgSAajbJhwwZyc3Pxer2q+5NYiBaLRbnPaWlpeL1e1TvA6XTGdJnX3XMpE3U6nSreJi+BLmfSda5isYhIXWRE4XBYFSsYhkEoFKK9vR2fz6cy/SJQDwQCuN1umpqaqKys5P3332fjxo1qUBjs0DPyO3fu5J///CennXYaxcXF7N69m7a2Njwej+pKVVtbqybR0xNFoiMWj0IIWJrOSLgFiLl2kpyKtwyFePUB2WKxUFdXh2EYSuJmGIaq449Go+r+Wq1WAoEAu3btoq6uTiVS46dmGQjoRxHls7DyAjOjvqhVyavMTlNgc7Zw2C1v8fbM6dQ8DCyFjVUjWZgfOy1JkHQA3ts4lbIxH+EnkygO6vAxmvX7dygV7NGULgUugvo1xdRTbP79TDHfP01TBuzG9PKxmbKqzacAD3+uqzDQYRgGtbW1rF+/nuLiYtrb28nOzo4R60tnIbFg9OmI5UWNLzkVlzw7Ozsmnqe3eIvP+EtCDIiZp0q0tGIxS8civbWfbCMSieD3+/H7/WzcuJGNGzeqLlWDEfFhErEGo9Gouj8vvvgiRx11FDk5OTQ0NFBXV4fD4VCusrj9EnutqqpSzaOlO5U0QpGeEB0d5jQ0IteSUlcgZlYHSTrJ8yLtAlNSUsjMzIxpLykd/SWDLzHWcDhMbW2tquZbs2YNa9asYceOHQQCAUXoe7NA9xbD72n0I6lWQu16WDwazrXxsOdiPLNrTJIlTOtsO3lUm/rWmY1wkxfrzHbyqIrZynpG8/FhE+FS+GzxGG5fcgWbPhoPk+GnzTfttbOUn0zWXXA4PLAK+BgzMGrAYxZzuhQPpiUNtDdr8xWtAFa8BVTB5sEpmzoQtLW1sXPnTjZs2IDT6SQ7O1tlYCU+p1dciQsuL6soBvTYn7h6UocPqJZ8euWNTrAioZEEmbiQYvGmp6cr0pTEiC6PkqRVXV0dW7Zs4eOPP1Yll18m6FZna2srr7/+Ok6nk5kzZ1JaWqpISrpI6Q1qRHKmS80k6y6Dk9xvQMXWnU5nTPtG3fWWWKx0yZLP7HY7WVlZqqNWc3MzqampBINB1WlMQkm1tbW0tbWxZcsW1q9fT01NzV573vYVgSZCP5f7PAernobNV8EzENqca0qV3nQDEWWFcq7XLGkFWnDEbGEYm8l9fxs1uQdBAWxaOx4p87/Tch13GwvJp4r1jGbR47dx/rfv4SW+TnVTHr9J+4lZp8/LwBGY4tNG8LvA74aFrUAVzCjhwZ9dCrfDs8ef0Un82cCzvXt5BggMw8Dv97N6tdmxSyqs5IXTW7yJixcOh0lJSVGzseqJK4n7SXtAvetQXl6e6sMq5CvVUA6HA8MwVCtCvWKqvr5etYyrra3F4/EQiUTUxHVCFp999hlbt26lsrJStTcciOgpUmhra+OTTz7BZrNRXFzMGWecoQYWsVKlabVe8STFAICyUmGPJ6GXhkp7SBnUJLapV9PZ7XYyMzNpb29XM9RKUxSJx0YiERWWkO2HQiGqq6vZtWsXNTU1bNy4ke3bt6v7urf711/EajH2c68Wy6LePZKZi8wk0MmrYOxUM1Z5aStgdn1irI2SDzfhb8rkT2nfU197na+xeMg1sMOA2ZY9U1uvAiI74KYSnrj2FIKk8yuu5bONY8xWhBEo/dEGtj4+CtogY85uAs58cxtPrQTnDIisAqbAyTZYhGm5jgKzb+sNvXo5DGPRF95GTwfkLRYLWVlZTJkyhaOOOorMzEyVdU9JMWdgdTqdqsuTtIUT69LtdisLU+JjgUBAZY/b29vJzc2lsLBQWS+SnYc9Daily1JzczOVlZXs3r2bxsZGJdkKh8NkZ2dz0EEHKcunrq6Od955h7ffflt1Mupp9NQLLLpZGYAOZP+JtKbigufl5XHppZdy3HHHUVhYiN/vZ/v27QQCATUFi7j2Pp9PeRwpKSmqg5gMTo2NjaqpiYRaiouLVfd+kXDJPFfyLNjtdrZu3aoSVDabjVAopDyWkSNHkpubS3t7OzU1NXz88cesWrWK999/n1AopMJGenvCRMmo+OsCe9QR0pdVNM6bN2/+IrerCwZOYfoLm+DN4cBE0+U/ElhnM8MDD7wLyycxm7+zLPU7vMBMHqhayGP58/gar7Ni+yZ2DBkOT4HZvCQVyt1wTwnnzzKbteykiM/+MMZMSC0EPJi1/JlAAcxyPM8TY+ebjbFrZ8AqAzjaPLZnWqHEZrr9mYB/8Ew33ZMwDLPj0WeffUZxsVmKK+Jt+S3uv7iEQrrSi1XcTJk5U0IG0jJQr/jRiUGfL0qyw+LyCxnU1NSo70QiEWpqatT0H7t372bz5s3U19cPmrr+noBeIlpfX8///vc/GhsbOfLII9UU0KIdlTmjZCodsRbF9ReXXcpNpc2fxMv1Bi0SR5VyYSkHzsvLU659c3MzDQ0Nqu2gxWLOObVlyxaqq6v57LPP8Pv91NTUqIIN0aH2tUzqQDBwSJVHOq1MG2y41kwEldCpCZ0Efrin8odwpJM/rvwhJw4zhfkfMI5TeJolKy83pz+5wws7/guby+GENqKGGS4Ywnauu/D/WHbhd9h62ShT0jUHeAbwr+KJofMp2/IRn704Bla9hVm/n49J0k/CfW1AFaawf/B0nepptLW1UVFRQWpqKqFQSDU9likxRColU3tIY2FJJkn7N4vFgsfjIRgMxvRulbmPRAMr03m0tLTg9/tVHFfaD0ooQJpf+/1+Zf289dZb1NXVqbp+qQj7MiMRycjA1dzczOrVq9m1axe7du1i4sSJDB06VLntUhAgEiYhSqOzVFQIUy9Blay73tRa1AGAUnoIadvtdnw+nwoZyb2TgVkkUtu2bWP9+vUqBNDU1KQapiQ614FErgOIVAWtsPufcG4VLLjAbKV3E5w8/a888/iZsKMKVuczbNhm2rBy069uhrHssSKfA249HpYbcLIFqznPCm7CHMqHbF07qjM0ACzvtEAfmAqPwWe/G2MS+YopZoJqdxWwJO74vrqEKohGo3z22WdEo1FKSkooLy/HbrdTX1+v4qHSWk+alXi9XmCPtatrSFNSzAnipOxQMtciNJdESVNTkyq5FNmPdC2SjkwSg92+fTvvvfeemjr7q4BE5b96SEDimX6/n82bN/Pvf/+bsrIyLrjgAqZPn059fT0NDQ0Ayh13uVwUFBTENCgX91n64UqIRiddCelI3F069ksjaQkdpKSkqGRVY2Mj77zzDq+//rrqwaD3mZDz2Ze7398YgKQKZqlnttkByg+kwjPpZ5pypwX5MA/uabuSr50zm+nXPsfL15xgrjsVM9G1/IPO7RxKCw6iOGjHipV2lo7/Ngv8jwNbgM2wY6Jpsa70mTFTPzCzCniLL6v2tCcQjUapqjKVGDk5OUr6IvHTlJQUVect2X8JD0imVyRYbW1tKk6mrwd7JgGUdoOwp2uSZJv1iQOlYKGmpqbfppgeSNCTNfK3WHvNzc3s2rWLf/3rX2oam9zcXHXfRP+Zl5cH7GmpaLFYVIy1qqqKaDSqJuATzyK+h4PU+nd0dNDQ0EB1dTWNjY3qHkmYZu3atQQCgZiigESd/AcyBiipAtTDhl8BeeC/AEKb4J7hpqaUVg4550Pu5oe8cdixpiu/GHgThn+8lk0zx5szsYbgUcs3ePSF75myrEu93H33QsZueYd1llooPxE2b4GCg82Cg+fuAmyYUoMvv1Tqi6Cjo0O57pFIhNLSUgoKCsjJyeGggw5S7ff8fr+yRhsaGkhNTVUNkwE1p7xIoKTJh2gP9ZJHyTBLomTbtm0EAgHV3q+uro66ujp2797Nzp07B3y3qd5CfNY7vrxXiFWkSu+99x4ul4vDDz+c8vJyNRtDZmYmgCpdlT4AuqdQX1+vplKR2RSkMbgMjBIzr6urU4S9adMmqqqqVDIsGo0SCATYuXNnTDiou96o+4uvdvZ/nxgHqd8yLdEjE3wcYU8IYBRmtr4As6uUE7MC6kgo+ekmAHb8Ybi5/guLMKds7dkM4BfFQMz+720/Yqnk5uYyfvx4ysrKSE1NJRqNkp+fr+Q0drtdvdAul0u1p5PEREZGBsOGDVOJDr2LvN5JSl7SjRs3EggEVKJLShgllNCX6Mnsv1448UURvw35X5qMS2u93NxcjjvuOGbMmKHi1WJhhkIhVYAhUjSHw6HUAgCFhYUqTCNdxOReh0Ih1bAmHA7z8ccfU19fr8I1eof/7toJ6sv25zzjl+mysK9G9n+f2Aptf4OFU4AqGDXJ7G41Abj6Xbh60h6ynV0FPAvlC0yXHlTLvh1/Gw5z1mPqqsZ1fjiwCHWwwTAMRWQiwamrq4vpc1lSUqKyykCMFSnZfbGgQqGQso7khRNXsK6ujvr6esLhMDt27KCiokJ1pYdYYXoSXZEo3ipJrNraWl588UUqKysZM2YMI0aMICcnR91fGTyFLGWuKal0CwQCMfX8Mr+UNDyRJFQoFKKuro5wOKwSm/rgKdgbeQ7UeCoMKks1HtJdPwhMB15jTwx0CmZMVH7Ho7vlAweDyVKNh17nb7VaSU9Pp7i4mKysLNVoWEpXZQZO0auKhZqWlkZWVpYqbwwEAmoCO+lcL+GHgYKBaqnqSLQ9ydhbLBbcbjfp6ekUFBRQVFREVlZWTFWbxLhFJiehABnUdMIVlYY0BZcElVTBSa+G+KY7gu6s089rqfaVTnUQk+qXG4OZVOMhLqa8kPHZYbFG9RdWyhqlS5JYwSLBOZDJ3foKg4FUBfq29bi1PoeY1PDr80vprf70Vo069Jiu3FuJk0tpqW6V7g9h7utZ7u469QepDiL3P4nBCl2PeCCor0+qL/oCujutN8rRBzpZD7rXwuoEq5O2HmbY2zQnXxYkSTWJJL6CiCfGRJ3BhAgTybK6I9bukKivbqLj+DzY234T1f/HJ756GklSTSKJAYYDteS6I8j9/V58mEGvld/ffR7I/hL935vNT+IHBX15b5BrklSTSCKJA8L+EFG8NvbzxkT3hYEYSkiSahJJDEDsb5IqEVkdqNW3NwuyJ9Cbrnai0tz9/U5vIUmqSSQxwDAQrS8d+0NKA/EcvgKd/5NIIokviv4gr8+TqOrNYxloSJJqEkkMMMTHI/XfSRwYEiXgevtaJkk1iSQGIHRXdbAQaiLp0hdVMnS37b2t39/XK0mqSSQxwBDfRKQ/J7E7EHSXNOutbe/PuomuW6ImLT2JJKkmkcQAg/Q/gMTuK/R/CXJvakoPZH+fR6MrPSakBLenkSTVJJIYYLDZbN02GUmEL0qwg8EK/iKIT6xJAxlpfdjTSJJqEkkMMOiW6r7QU6TwZSdWiC2N1ZvF9Ph+9rdLVRJJJJFEEvtGSn8fQBJJJJHElwlJUk0iiSSS6EEkSTWJJJJIogeRJNUkkkgiiR5EklSTSCKJJHoQSVJNIokkkuhBJEk1iSSSSKIHkSTVJJJIIokeRJJUk0giiSR6EP8PfEkoV38zIiIAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 400x150 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation: kld: 355.282043 ;perceptual: 0.298079 ;generator: 2.436252 ;feature: 0.092646;discriminator: 3.304899 \n",
      "Epoch 70/100\n",
      "Train: kld: 2114.680328 ;perceptual: 1.984997 ;generator: 9.729830 ;feature: 0.097256 ;discriminator: 1.519881 \n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x150 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation: kld: 330.348267 ;perceptual: 0.333957 ;generator: 1.760911 ;feature: 0.078033;discriminator: 3.274506 \n",
      "Epoch 80/100\n",
      "Train: kld: 4189.280212 ;perceptual: 1.892120 ;generator: 9.799735 ;feature: 0.064589 ;discriminator: 1.890061 \n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x150 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation: kld: 448.618286 ;perceptual: 0.370321 ;generator: 0.966575 ;feature: 0.069611;discriminator: 3.678246 \n",
      "Epoch 90/100\n",
      "Train: kld: 3836.584351 ;perceptual: 1.578433 ;generator: 14.984342 ;feature: 0.070032 ;discriminator: 1.865685 \n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x150 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation: kld: 860.845093 ;perceptual: 0.301508 ;generator: 2.683611 ;feature: 0.085221;discriminator: 3.374906 \n"
     ]
    }
   ],
   "source": [
    "net = net.to(device)\n",
    "discriminator = discriminator.to(device)\n",
    "torch.autograd.set_detect_anomaly(True)\n",
    "losses = {\"kld\": [], \"perceptual\": [], \"feature\": [], \"generator\": [], \"discriminator\": []}\n",
    "losses_val = {\"kld\": [], \"perceptual\": [], \"feature\": [], \"generator\": [], \"discriminator\": []}\n",
    "for epoch in range(max_epochs):\n",
    "    if epoch % 10 == 0:\n",
    "        print(\"Epoch %d/%d\" % (epoch, max_epochs))\n",
    "    losses_epoch = {\"kld\": 0, \"perceptual\": 0, \"feature\": 0, \"generator\": 0, \"discriminator\": 0}\n",
    "    for d in train_loader:\n",
    "        image = d[\"image\"].to(device)\n",
    "        with torch.no_grad():\n",
    "            label = one_hot(d[\"label\"], 10).to(device)\n",
    "        optimizer_g.zero_grad()\n",
    "\n",
    "        # Losses gen\n",
    "        out, mu, logvar = net(label, image)\n",
    "        kld_ = kld_loss(mu, logvar)\n",
    "        disc_fakes, features_fakes = discriminator(torch.cat([out, label], 1))\n",
    "        loss_g = adversarial_loss(disc_fakes, target_is_real=True, for_discriminator=False)\n",
    "        disc_reals, features_reals = discriminator(torch.cat([image, label], 1))\n",
    "        loss_feat = feature_loss(features_fakes, features_reals, lambda_feat, device)\n",
    "        loss_perc = perceptual_loss(out, target=image)\n",
    "        total_loss = loss_g + loss_perc * lambda_perc + kld_ * lambda_kld + loss_feat * lambda_feat\n",
    "        total_loss.backward(retain_graph=True)\n",
    "        optimizer_g.step()\n",
    "\n",
    "        # Store\n",
    "        losses_epoch[\"kld\"] += kld_.item()\n",
    "        losses_epoch[\"perceptual\"] += loss_perc.item()\n",
    "        losses_epoch[\"generator\"] += loss_g.item()\n",
    "        # Train disc\n",
    "        out, _, _ = net(label, image)\n",
    "        disc_fakes, _ = discriminator(torch.cat([out, label], 1))\n",
    "        loss_d_r = adversarial_loss(disc_reals, target_is_real=True, for_discriminator=True)\n",
    "        loss_g_f = adversarial_loss(disc_fakes, target_is_real=False, for_discriminator=True)\n",
    "        optimizer_d.zero_grad()\n",
    "        loss_d = loss_d_r + loss_g_f\n",
    "        loss_d.backward()\n",
    "        optimizer_d.step()\n",
    "\n",
    "        # Store\n",
    "        losses_epoch[\"feature\"] = loss_feat.item()\n",
    "        losses_epoch[\"discriminator\"] = (loss_d_r.item() + loss_g_f.item()) / 2\n",
    "\n",
    "    if epoch % 10 == 0:\n",
    "        msgs = [\n",
    "            f\"Train: kld: {np.mean(losses_epoch['kld']):4f} \",\n",
    "            f\"perceptual: {np.mean(losses_epoch['perceptual']):4f} \",\n",
    "            f\"generator: {np.mean(losses_epoch['generator']):4f} \",\n",
    "            f\"feature: {np.mean(losses_epoch['feature']):4f} \",\n",
    "            f\"discriminator: {np.mean(losses_epoch['discriminator']):4f} \",\n",
    "        ]\n",
    "        print(\";\".join(msgs))\n",
    "\n",
    "    losses_epoch_val = {\"kld\": 0, \"perceptual\": 0, \"feature\": 0, \"generator\": 0, \"discriminator\": 0}\n",
    "    for d in val_loader:\n",
    "        image = d[\"image\"].to(device)\n",
    "        with torch.no_grad():\n",
    "            label = one_hot(d[\"label\"], 10).to(device)\n",
    "            # Losses gen\n",
    "            out, mu, logvar = net(label, image)\n",
    "            kld_ = kld_loss(mu, logvar)\n",
    "            disc_fakes, features_fakes = discriminator(torch.cat([out, label], 1))\n",
    "            loss_g = adversarial_loss(disc_fakes, target_is_real=True, for_discriminator=False)\n",
    "            disc_reals, features_reals = discriminator(torch.cat([image, label], 1))\n",
    "            loss_feat = feature_loss(features_fakes, features_reals, lambda_feat, device)\n",
    "            loss_perc = perceptual_loss(out, target=image)\n",
    "            total_loss = loss_adv * loss_g + loss_perc * lambda_perc + kld_ * lambda_kld + loss_feat * lambda_feat\n",
    "            # Store\n",
    "            losses_epoch_val[\"kld\"] += kld_.item()\n",
    "            losses_epoch_val[\"perceptual\"] += loss_perc.item()\n",
    "            losses_epoch_val[\"generator\"] += loss_g.item()\n",
    "            # Train disc\n",
    "            out, _, _ = net(label, image)\n",
    "            disc_fakes, _ = discriminator(torch.cat([out, label], 1))\n",
    "            loss_d_r = adversarial_loss(disc_reals, target_is_real=True, for_discriminator=True)\n",
    "            loss_g_f = adversarial_loss(disc_fakes, target_is_real=False, for_discriminator=True)\n",
    "            loss_d = loss_adv * (loss_d_r + loss_g_f)\n",
    "\n",
    "            # Store\n",
    "            losses_epoch_val[\"feature\"] = loss_feat.item()\n",
    "            losses_epoch_val[\"discriminator\"] = loss_d_r.item() + loss_g_f.item()\n",
    "\n",
    "    if epoch % 10 == 0:\n",
    "        picture_results(label, image, out)\n",
    "        msgs = [\n",
    "            f\"Validation: kld: {np.mean(losses_epoch_val['kld']):4f} \",\n",
    "            f\"perceptual: {np.mean(losses_epoch_val['perceptual']):4f} \",\n",
    "            f\"generator: {np.mean(losses_epoch_val['generator']):4f} \",\n",
    "            f\"feature: {np.mean(losses_epoch_val['feature']):4f}\",\n",
    "            f\"discriminator: {np.mean(losses_epoch_val['discriminator']):4f} \",\n",
    "        ]\n",
    "        print(\";\".join(msgs))\n",
    "\n",
    "    for key, val in losses_epoch.items():\n",
    "        losses[key].append(val / len(train_loader))\n",
    "    for key, val in losses_epoch_val.items():\n",
    "        losses_val[key].append(val / len(val_loader))"
   ]
  }
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